Future Earth and EcoHealth: A New Paradigm Toward Global Sustainability and Health
Bibliographic record
Abstract
Concurrent with the sustainable development goals adoption and the UN Climate negotiations, 2015 also marked the formal establishment of the Future Earth scientific platform, envisioned as a 10-year research program for global sustainability.Future Earth merges previous scientific programs in the global environmental change realmincluding biodiversity science from DIVERSITAS, the International Geosphere-Biosphere Programme, and the International Human Dimensions Programme.The merging of programs offers a way to reduce redundancy, but even more powerfully, a way to bring together seemingly disparate facets of global change research communities to work more collaboratively.Accordingly, Future Earth seeks to encourage fundamental scientific work, integrate sciences across disciplines, especially incorporating the social sciences, humanities, and health and engineering sciences.It also seeks co-designing science projects with stakeholders such as users and funders to develop solutions oriented research.We intend to catalyze new relationships and a new model for research.A key to our success is co-design and co-production of knowledge-the upfront joint creation of research questions that can lend more ready application of findings by potential users.Governments, industry, and civil society are our key stakeholders.Future Earth is not starting from scratch; it is built on the existing critical research that has shown the many effects of anthropogenic forces on our health and environment and the need for action.Through its core projects, it maintains the importance of continued fundamental scientific knowledge generation.Research is spread across three themes-'Dynamic Planet, ' 'Global Sustainable Development,' and 'Transformations Toward Sustainabil-
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.032 | 0.034 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".